Clusterer.h

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#ifndef GRT_CLUSTERER_HEADER
#define GRT_CLUSTERER_HEADER

#include "MLBase.h"

GRT_BEGIN_NAMESPACE

class GRT_API Clusterer : public MLBase
{
public:
 Clusterer(void);
 
 virtual ~Clusterer(void);
 
 virtual bool deepCopyFrom(const Clusterer *clusterer){ return false; }
 
 bool copyBaseVariables(const Clusterer *clusterer);
 
 virtual bool train_(MatrixFloat &trainingData);
 
 virtual bool train_(ClassificationData &trainingData);
 
 virtual bool train_(UnlabelledData &trainingData);
 
 virtual bool reset();
 
 virtual bool clear();
 
 bool getConverged() const;
 
 UINT getNumClusters() const;
 
 UINT getPredictedClusterLabel() const;
 
 Float getMaximumLikelihood() const;
 
 Float getBestDistance() const;
 
 VectorFloat getClusterLikelihoods() const;
 
 VectorFloat getClusterDistances() const;
 
 Vector< UINT > getClusterLabels() const;

 std::string getClustererType() const;
 
 bool setNumClusters(const UINT numClusters);
 
 typedef std::map< std::string, Clusterer*(*)() > StringClustererMap;
 
 static Clusterer* createInstanceFromString( std::string const &ClustererType );
 
 Clusterer* createNewInstance() const;
 
 Clusterer* deepCopy() const;
 
 const Clusterer& getBaseClusterer() const;

 static Vector< std::string > getRegisteredClusterers();
 
 //Tell the compiler we are explicitly using the following classes from the base class (this stops hidden overloaded virtual function warnings)
 using MLBase::train;
 
protected:
 bool saveClustererSettingsToFile( std::fstream &file ) const;
 
 bool loadClustererSettingsFromFile( std::fstream &file );

 std::string clustererType;
 UINT numClusters; 
 UINT predictedClusterLabel; 
 Float maxLikelihood;
 Float bestDistance;
 VectorFloat clusterLikelihoods;
 VectorFloat clusterDistances;
 Vector< UINT > clusterLabels;
 bool converged;
 Vector<MinMax> ranges;
 
 static StringClustererMap *getMap() {
 if( !stringClustererMap ){ stringClustererMap = new StringClustererMap; } 
 return stringClustererMap; 
 }
 
private:
 static StringClustererMap *stringClustererMap;
 static UINT numClustererInstances;
 
};
 
//These two functions/classes are used to register any new Classification Module with the Clusterer base class
template< typename T > Clusterer* getNewClassificationModuleInstance() { return new T; }

template< typename T >
class RegisterClustererModule : Clusterer { 
public:
 RegisterClustererModule( const std::string &newClassificationModuleName ) { 
 getMap()->insert( std::pair< std::string, Clusterer*(*)() >(newClassificationModuleName, &getNewClassificationModuleInstance< T > ) );
 }
};

GRT_END_NAMESPACE

#endif //GRT_CLUSTERER_HEADER